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      Python+OpenCV教程1：简介与安装
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	Posted on <a href="/opencv-python-introduction-and-installation/" class="article-date">
	  <time datetime="2017-12-06T07:50:59.000Z" itemprop="datePublished">December 6, 2017</time>
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        <p>相信大部分人知道的OpenCV都是用C++来开发的，那为什么我推荐使用Python呢？<a id="more"></a></p>
<blockquote>
<p>本教程翻译自<a href="http://opencv-python-tutroals.readthedocs.io/en/latest/index.html" target="_blank" rel="external">OpenCV官方英文教程</a>，我按照使用度和难易度翻译，重新编写了大量原创内容，将不常用和较难的部分写成番外篇，浅显易懂，很easy的辣。每节的源码、图片和练习题答案均可在<a href="#引用">引用</a>处找到噢(⊙o⊙)</p>
</blockquote>
<hr>
<h2 id="Python照样快！"><a href="#Python照样快！" class="headerlink" title="Python照样快！"></a>Python照样快！</h2><p>众所周知，虽然Python语法简洁，编写高效，但相比C/C++运行慢很多。然而Python还有个重要的特性：它是一门胶水语言！Python可以很容易地扩展C/C++。<strong>OpenCV-Python</strong>就是用Python包装了C++的实现，背后实际就是C++的代码在跑，所以代码的运行速度跟原生C/C++速度一样快。</p>
<p>我举两个简单的例子就一目了然了：一个是读入图片，另一个是调整图片的对比度和亮度：</p>
<p><img src="http://pic.ex2tron.top/cv2_python_vs_cplus_speed.jpg" alt=""></p>
<p><strong>可以看到某些情况下Python的运行速度甚至好于C++，代码行数也直接少一半多！</strong>另外，图像是矩阵数据，OpenCV-Python原生支持<a href="https://baike.baidu.com/item/numpy" target="_blank" rel="external">Numpy</a>，相当于Python中的Matlab，为矩阵运算、科学计算提供了极大的便利性。</p>
<h2 id="人工智能浪潮"><a href="#人工智能浪潮" class="headerlink" title="人工智能浪潮"></a>人工智能浪潮</h2><p>近些年，人工智能相关技术的快速发展大家有目共睹，不必多说。在编程语言方面，更多人希望的是具备高效开发效率、跨平台、高度扩展性的语言，尤其是一些AI巨头优先推出支持Python语言的深度学习框架，如Facebook的<a href="https://pytorch.org/" target="_blank" rel="external">PyTorch</a>、Google的<a href="https://tensorflow.google.cn/" target="_blank" rel="external">Tensorflow</a>等，可以说Python是名副其实的“网红语言”了。</p>
<p><img src="http://pic.ex2tron.top/cv2_ai_ml_dl2.jpg" alt=""></p>
<p>从<a href="https://www.tiobe.com/tiobe-index/" target="_blank" rel="external">TIOBE编程语言排行榜</a>也可以看到，Python发展迅猛，已经逼近C++的份额。这个排行榜每月更新，我就不截图了，编写时TOP5：Java/C/C++/Python/C#。</p>
<h2 id="人生苦短，我用Python"><a href="#人生苦短，我用Python" class="headerlink" title="人生苦短，我用Python"></a>人生苦短，我用Python</h2><ul>
<li>如果你搞科研用，果断放弃C++（Matlab？出门左拐）</li>
<li>如果你是快速原型开发，验证方案，果断放弃C++</li>
<li>如果你懒的配置OpenCV环境，果断放弃C++</li>
<li>如果你的程序是在支持Python的较高硬件环境下运行，果断放弃C++</li>
<li>如果你担心Python写不了界面，那是你的问题o_o ….</li>
<li>除非你的程序是MFC或已经用C++编写其他模块或是嵌入式设备，那就用C++吧</li>
</ul>
<p><strong>“人生苦短，我用Python！！！”</strong></p>
<h2 id="安装"><a href="#安装" class="headerlink" title="安装"></a>安装</h2><blockquote>
<p>本教程编写时使用的软件版本是：OpenCV 3.x，Python 3.x。</p>
</blockquote>
<p>要安装OpenCV，只需cmd下的一条指令：</p>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><div class="line">1</div></pre></td><td class="code"><pre><div class="line">pip install opencv-python</div></pre></td></tr></table></figure>
<p>pip是Python的包管理器，如果你还没安装Python，强烈推荐安装<a href="https://www.anaconda.com/download/" target="_blank" rel="external">Anaconda</a>，它包含了大量的科学计算包，不用后期一个个安装。即使你已经装了Python也没有影响，Anaconda相当于虚拟环境，互不干扰。</p>
<h3 id="安装步骤"><a href="#安装步骤" class="headerlink" title="安装步骤"></a>安装步骤</h3><p>进入Anaconda<a href="https://www.anaconda.com/download/" target="_blank" rel="external">官网</a>，下载最新版本的安装文件，速度比较慢的话，可以去<a href="https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/" target="_blank" rel="external">清华开源镜像站</a>。</p>
<ul>
<li><p>Windows版下载的是exe文件，双击可以直接安装，安装时记得勾选 <code>Add Anaconda to my PATH environment variable</code>，添加到环境变量中。</p>
</li>
<li><p>Linux版下载的是sh文件，下载完成后，终端切换到下载目录，执行<code>bash Anaconda3-xx.sh</code>，Linux版也会提示添加环境变量，记得输yes就行。</p>
</li>
</ul>
<h3 id="安装测试"><a href="#安装测试" class="headerlink" title="安装测试"></a>安装测试</h3><p>Python安装好之后，可以在cmd中输入<code>python --version</code>来查看Python的版本信息。对于OpenCV，打开Python的开发环境，输入<code>import cv2</code>，运行没有报错说明一切正常。要查看OpenCV的版本，可以：</p>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><div class="line">1</div></pre></td><td class="code"><pre><div class="line"><span class="built_in">print</span>(cv2.__version__)  <span class="comment"># '3.4.1'</span></div></pre></td></tr></table></figure>
<blockquote>
<p>Python开发环境我用的是<a href="http://code.visualstudio.com/" target="_blank" rel="external">Visual Studio Code</a>，也可以用<a href="http://www.jetbrains.com/pycharm/" target="_blank" rel="external">PyCharm</a>/<a href="https://atom.io/" target="_blank" rel="external">Atom</a>/Jupyter Notebook(Anaconda自带)，或者直接在命令行里敲，自己习惯就行。</p>
</blockquote>
<h3 id="常见问题"><a href="#常见问题" class="headerlink" title="常见问题"></a>常见问题</h3><ol>
<li>pip识别不了：环境变量中没有pip的目录，找到pip目录，添加到用户（或系统）变量的path中。</li>
<li>下载速度很慢：可<a href="https://pypi.org/search/?q=opencv-python" target="_blank" rel="external">到此处</a>下载离线版。下载完成后，cmd切换到下载目录，输入 <code>pip install 文件名</code>安装。</li>
</ol>
<h2 id="学习软件"><a href="#学习软件" class="headerlink" title="学习软件"></a>学习软件</h2><p>为了便于学习OpenCV，我写了一个教学款软件<a href="https://github.com/ex2tron/LearnOpenCVEdu" target="_blank" rel="external">LearnOpenCVEdu</a>，目前只开发了一部分功能，有兴趣的童鞋可以支持一下噢😊</p>
<p><img src="http://pic.ex2tron.top/cv2_learn_opencv_edu_soft_screenshot.jpg" alt="大家随手点个Star吧(●ˇ∀ˇ●)"></p>
<blockquote>
<p>经验之谈：虽然从一开始我就推荐大家使用OpenCV-Python进行图像处理，但<em>想要深入理解OpenCV</em>，C++还是必须的，尤其是<strong>OpenCV源码</strong>！</p>
</blockquote>
<h2 id="引用"><a href="#引用" class="headerlink" title="引用"></a>引用</h2><ul>
<li><a href="https://github.com/ex2tron/OpenCV-Python-Tutorial/tree/master/01.%20%E7%AE%80%E4%BB%8B%E4%B8%8E%E5%AE%89%E8%A3%85" target="_blank" rel="external">本节源码</a></li>
</ul>
<h3 id="网络资料"><a href="#网络资料" class="headerlink" title="网络资料"></a>网络资料</h3><ul>
<li><a href="https://docs.opencv.org/" target="_blank" rel="external"><strong>OpenCV Docs官方文档</strong></a></li>
<li><a href="https://github.com/opencv/opencv" target="_blank" rel="external">OpenCV 官方Github</a></li>
<li><a href="http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html" target="_blank" rel="external">官方英文教程：OpenCV-Python Tutorials</a></li>
<li><a href="http://www.learnopencv.com" target="_blank" rel="external">LearnOpenCV</a>、<a href="https://github.com/spmallick/learnopencv" target="_blank" rel="external">LearnOpenCV Github</a></li>
<li><a href="https://docs.scipy.org/doc/numpy-dev/user/quickstart.html" target="_blank" rel="external">Numpy Quickstart Tutorial</a></li>
<li><a href="http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/tutorials.html" target="_blank" rel="external">OpenCV 中文教程</a></li>
</ul>
<h3 id="书籍"><a href="#书籍" class="headerlink" title="书籍"></a>书籍</h3><ul>
<li><a href="http://programmingcomputervision.com/" target="_blank" rel="external">Programming Computer Vision with Python</a>、<a href="https://www.amazon.cn/dp/B00L3Y3NEM/ref=sr_1_1?ie=UTF8&amp;qid=1543929834&amp;sr=8-1&amp;keywords=Python+%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89" target="_blank" rel="external">中文书</a></li>
<li><a href="https://www.pyimagesearch.com/practical-python-opencv/" target="_blank" rel="external">https://www.pyimagesearch.com/practical-python-opencv/</a></li>
</ul>
<h3 id="名校视觉研究所-课程"><a href="#名校视觉研究所-课程" class="headerlink" title="名校视觉研究所/课程"></a>名校视觉研究所/课程</h3><ul>
<li><a href="http://graphics.cs.cmu.edu/" target="_blank" rel="external">卡内基梅隆大学</a></li>
<li><a href="https://www.cs.toronto.edu/~guerzhoy/320/" target="_blank" rel="external">多伦多大学</a></li>
</ul>

      
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      <ol class="nav"><li class="nav-item nav-level-2"><a class="nav-link" href="#Python照样快！"><span class="nav-number">1.</span> <span class="nav-text">Python照样快！</span></a></li><li class="nav-item nav-level-2"><a class="nav-link" href="#人工智能浪潮"><span class="nav-number">2.</span> <span class="nav-text">人工智能浪潮</span></a></li><li class="nav-item nav-level-2"><a class="nav-link" href="#人生苦短，我用Python"><span class="nav-number">3.</span> <span class="nav-text">人生苦短，我用Python</span></a></li><li class="nav-item nav-level-2"><a class="nav-link" href="#安装"><span class="nav-number">4.</span> <span class="nav-text">安装</span></a><ol class="nav-child"><li class="nav-item nav-level-3"><a class="nav-link" href="#安装步骤"><span class="nav-number">4.1.</span> <span class="nav-text">安装步骤</span></a></li><li class="nav-item nav-level-3"><a class="nav-link" href="#安装测试"><span class="nav-number">4.2.</span> <span class="nav-text">安装测试</span></a></li><li class="nav-item nav-level-3"><a class="nav-link" href="#常见问题"><span class="nav-number">4.3.</span> <span class="nav-text">常见问题</span></a></li></ol></li><li class="nav-item nav-level-2"><a class="nav-link" href="#学习软件"><span class="nav-number">5.</span> <span class="nav-text">学习软件</span></a></li><li class="nav-item nav-level-2"><a class="nav-link" href="#引用"><span class="nav-number">6.</span> <span class="nav-text">引用</span></a><ol class="nav-child"><li class="nav-item nav-level-3"><a class="nav-link" href="#网络资料"><span class="nav-number">6.1.</span> <span class="nav-text">网络资料</span></a></li><li class="nav-item nav-level-3"><a class="nav-link" href="#书籍"><span class="nav-number">6.2.</span> <span class="nav-text">书籍</span></a></li><li class="nav-item nav-level-3"><a class="nav-link" href="#名校视觉研究所-课程"><span class="nav-number">6.3.</span> <span class="nav-text">名校视觉研究所/课程</span></a></li></ol></li></ol>
    
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